Instructions to use suimu/VIRES_VAE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use suimu/VIRES_VAE with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image, export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("suimu/VIRES_VAE", dtype=torch.bfloat16, device_map="cuda") pipe.to("cuda") prompt = "A man with short gray hair plays a red electric guitar." image = load_image( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png" ) output = pipe(image=image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Improve model card with metadata and links (#1)
Verified signature- Improve model card with metadata and links (102d328e48f183e103f86c5f3003fd5c73c8a978) Co-authored-by: Niels Rogge <nielsr@users.noreply.huggingface.co>9e93a6c
-
Create README.md
Verified signature6e83386
-
Upload diffusion_pytorch_model.safetensors
Verified signature0af7da4 -
Remove .DS_Store file
e5527e8 -
sdxl
e82d140 -
Upload 4 files
Verified signature3a68bf6 -
initial commit
Verified signaturee7fdeff